Development of the Near-Term Forecast of Inflation for Uzbekistan: Application of FAVAR and BVAR models

Temurbek Boymirzaev
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Temurbek Boymirzaev: Central Bank of Uzbekistan

No 06-2025, IHEID Working Papers from Economics Section, The Graduate Institute of International Studies

Abstract: This study investigates the application of Factor-Augmented Vector Autoregression (FAVAR) and Bayesian Vector Autoregression (BVAR) models for inflation forecasting. FAVAR models deal with high-dimensional data by extracting latent factors from extensive macroeconomic indicators, while BVAR models incorporate prior distributions to enhance forecast stability and precision in data-limited environments. Employing a comprehensive dataset of Uzbekistan-specific inflation determinants, we conduct an empirical assessment of both models, examining their predictive accuracy. Findings from this research aim to optimize inflation forecasting methodologies, providing the Central Bank of Uzbekistan with robust, data-driven insights for improved policy formulation.

Keywords: FAVAR; BVAR; inflation forecast; forecast combination (search for similar items in EconPapers)
JEL-codes: E30 E31 E37 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2025-02-27
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